Whether you are launching a 50-SKU capsule collection on Shopify or managing a 10,000-SKU omnichannel catalog across Amazon, Zalando, Trendyol, and Etsy, inconsistent product photography and uncalibrated sizing visuals are the single biggest bottleneck to launch velocity.
To help e-commerce creative operations teams, studio photographers, and frontend engineers standardize their workflows, we have open-sourced four comprehensive, copy-paste operational checklists used across top-performing brands powered by Photta and Photta Business.
Feel free to copy these Markdown checklists directly into your team's Notion, Linear, Jira, or GitHub repository SOPs.
Checklist 1: Multi-Marketplace Image Technical Compliance Matrix (2026)
Every major e-commerce marketplace enforces automated computer-vision suppression rules on main hero images and secondary gallery slots. Failing these checks results in silent listing suppression or throttled ad impressions.
| Marketplace | Primary Hero Background | Aspect Ratio & Min Resolution | On-Model vs. Ghost Mannequin Policy | Color Profile & Format |
|---|---|---|---|---|
| Amazon Fashion | Pure White (RGB 255,255,255) | 1:1 or 3:4 (>= 1600px longest side for zoom) | Adult apparel: On-Model or 3D Ghost Mannequin (no flat-lays on main) | sRGB, JPEG/PNG/WebP (<10MB) |
| Shopify DTC | Brand Neutral (#F7F7F5 or Editorial) | 3:4 or 4:5 (2048 x 2560px recommended) | On-model lookbook + Ghost Mannequin + Live PDP Virtual Try-On | sRGB, WebP/AVIF (<350KB optimized) |
| Zalando Partner | Light Grey (#F3F3F3 / #EFEFEF) | 4:5 (1800 x 2250px) | Image 1: Full-body model; Image 2: Cutout / Ghost Mannequin packshot | sRGB, JPEG (85%+ quality) |
| Trendyol | Pure White or Studio Neutral | 2:3 (1200 x 1800px min) | On-model primary strongly preferred for clothing brands | sRGB, JPEG (<5MB) |
| Etsy | Natural Studio or Warm Editorial | 4:3 or 4:5 (>= 2000px shortest side) | Macro on-model lifestyle for online jewelry + scale reference | sRGB, JPEG/PNG |
Copy-Paste Pre-Upload QA Checklist
### [ ] Marketplace Image Pre-Flight QA - [ ] Primary packshot background verified at exact hex requirement (#FFFFFF for Amazon, #F3F3F3 for Zalando) - [ ] Product occupies between 80% and 85% of the total canvas frame (no edge clipping) - [ ] Color space explicitly converted to sRGB IEC61966-2.1 (never upload AdobeRGB or CMYK to web storefronts) - [ ] Zero watermarks, promotional badges, or text overlays on Image Slot #1 - [ ] File naming follows SEO/GEO slug convention: `brand-product-name-color-material-view.webp` - [ ] Descriptive `alt` attributes populated with fabric composition, cut, and color for AI search indexing Checklist 2: 3D Ghost Mannequin ("Hollow Man") Preparation SOP
Traditionally, creating a 3D hollow-man or invisible mannequin effect required shooting a garment on a matte white mannequin, turning it inside out to shoot the inner neck label on a foam board, and spending 20 minutes per SKU in Photoshop with the Pen Tool and Clone Stamp.
With Photta's AI Ghost Mannequin tool, you can generate a 3D hollow-man packshot from a single smartphone flat-lay or hanger photo in seconds. Use this preparation checklist to get 100% studio-grade accuracy on the first generation:
### [ ] AI Ghost Mannequin Source Photo Checklist - [ ] **Steaming & Pressing:** Garment is freshly steamed; remove harsh fold creases from factory polybags (keep natural fabric texture intact). - [ ] **Symmetrical Lay / Hanger Alignment:** - [ ] Shoulders aligned evenly on a thin matte hanger or laid flat on a contrasting neutral surface. - [ ] Sleeves angled slightly outward (15°–30° from torso) so sleeve cuffs do not overlap the main bodice. - [ ] Buttons, zippers, and plackets fully fastened and centered vertically. - [ ] **Neckline & Inner Collar Visibility:** - [ ] Back neck label and inner collar lining are unobstructed so the AI Ghost Mannequin synthesizer can reconstruct natural 3D depth. - [ ] **Lighting & Color Accuracy:** - [ ] Diffused, even illumination (avoid harsh directional window blinds or yellow tungsten bulbs that cast a color tint on white fabrics). - [ ] Camera held perpendicular (90°) to the garment plane to prevent keystone perspective distortion. - [ ] **Post-Generation Verification in Photta:** - [ ] Verify 3D inner-collar shadow depth and hemline curvature. - [ ] Export at 2x resolution in lossless PNG or WebP for marketplace packshot slot #2. Checklist 3: On-Model AI Fashion, Jewelry & Eyewear Studio Checklist
When generating on-model lookbooks using the AI Fashion Model Generator, Photta Jewelry Studio, or Photta Eyewear Studio, following a structured creative brief ensures visual consistency across your entire seasonal collection.
### [ ] AI On-Model Studio Production Checklist #### A. Brand Identity & Model Lock (`Model Maker`) - [ ] Define 2 to 3 core brand personas in Photta Model Maker (e.g., Primary Editorial Model, Inclusive Curve Model, Streetwear Model). - [ ] Lock consistent lighting direction and studio backdrop palette (e.g., Warm Concrete Studio, Parisian Daylight Loft, Pure Cyclorama). - [ ] Verify that model skin undertones complement the seasonal color palette. #### B. Apparel Micro-Detail QA - [ ] Confirm garment length landmark (cropped at waist, mid-hip, knee-length midi, or ankle-skimming maxi). - [ ] Inspect high-frequency details: button count, chest embroidery, contrast stitching, and fabric sheen match physical sample 1:1. - [ ] Generate 3 core angles per SKU: Front Full-Body, 3/4 Editorial Pose, and Close-Up Fabric Detail. #### C. Fine Jewelry & Eyewear True-Scale QA - [ ] **Necklaces:** Specify exact chain length in millimeters/inches (e.g., 16" choker vs. 18" princess length) in [Jewelry Studio](https://www.photta.app/tools/jewelry-studio). - [ ] **Earrings & Rings:** Verify tragus-to-lobe proportion and ring band width relative to finger knuckle geometry. - [ ] **Eyewear:** Confirm frame bridge width (e.g., 52-18-145mm) and lens tint translucency in [Eyewear Studio](https://www.photta.app/tools/eyewear-studio). Pro Tip on Budgeting Studio Runs: If you are comparing per-SKU generation costs across tools, inspect our transparent Botika pricing breakdown and FASHN AI review. Unlike rigid monthly plans where unused studio credits vanish on the 1st of the month, Photta's pricing includes non-expiring Pay-As-You-Go credit packs ideal for batch collection drops.
Checklist 4: Storefront Virtual Try-On Deployment, GDPR & GA4 Attribution SOP
Deploying live customer virtual try-on on your Product Detail Pages via Photta Business transforms passive window shoppers into high-intent buyers while cutting return rates by up to 34%.
Use this engineering and compliance checklist when rolling out the widget on Shopify, WooCommerce, or a custom headless storefront:
### [ ] B2B Storefront Virtual Try-On Launch Checklist #### 1. Security & Domain Firewall Configuration - [ ] Add production domain (`www.yourbrand.com`) and staging domain (`staging.yourbrand.com`) to Photta Business Origin Whitelist. - [ ] Enable edge rate-limiting (recommended: max 10 try-on generations per IP/session per 15-minute window). - [ ] Enable invisible hCaptcha challenge for suspicious automated traffic bursts. #### 2. Core Web Vitals & DOM Placement - [ ] Load widget script with `async defer` attributes (`<14KB` bootstrap; zero blocking impact on LCP). - [ ] Mount the "Try It On Virtually" trigger button directly below or adjacent to the primary "Add to Cart" CTA above the fold on mobile. - [ ] Pass clean SKU metadata attributes (`data-sku-id`, `data-product-image`, `data-product-category`). #### 3. GDPR, CCPA & KVKK Privacy Compliance - [ ] Verify `data-gdpr-ttl="3600"` is active so all shopper-uploaded selfies and generated composites auto-delete within 1 hour. - [ ] Link your store privacy notice to the [GDPR-Compliant Virtual Try-On specification](https://www.photta.app/business/guides/gdpr-compliant-virtual-try-on). - [ ] Confirm EXIF and GPS metadata stripping is enabled at edge upload. #### 4. Analytics & Return-Rate Cohort Attribution - [ ] Fire GA4 custom events on `photta:tryon:opened`, `photta:tryon:completed`, and `photta:tryon:add_to_cart`. - [ ] Append hidden line-item property `_tried_on_via_photta: true` to cart payloads. - [ ] Configure 30-day cohort dashboard comparing return rates and AOV of Try-On shoppers vs. Non-Try-On shoppers. Automated Image Pre-Flight Validation Script (Node.js)
Want to automatically validate your product image folder against marketplace resolution and aspect-ratio requirements before uploading to Shopify or running batch jobs through the Photta vs FASHN AI benchmarked REST API?
Drop this lightweight Node.js script into your CI/CD or catalog pipeline:
// validate-catalog-images.mjs import fs from 'node:fs/promises'; import path from 'node:path'; const MIN_WIDTH = 1600; const MIN_HEIGHT = 2000; // 4:5 aspect ratio target async function auditCatalogDirectory(dirPath) { const files = await fs.readdir(dirPath); const imageFiles = files.filter((f) => /\.(webp|jpg|jpeg|png)$/i.test(f)); console.log(`Auditing ${imageFiles.length} catalog images in ${dirPath}...`); for (const file of imageFiles) { const stats = await fs.stat(path.join(dirPath, file)); const sizeKb = Math.round(stats.size / 1024); if (sizeKb > 500 && file.endsWith('.webp')) { console.warn(`[WARN] ${file} is ${sizeKb}KB — consider optimizing below 350KB for Shopify LCP.`); } else { console.log(`[PASS] ${file} (${sizeKb}KB) ready for Photta Studio & PDP deployment.`); } } } auditCatalogDirectory('./catalog-ready'); By combining standardized pre-flight checklists, automated studio generation at Photta, and live PDP virtual try-on via Photta Business, e-commerce teams can cut sample-to-storefront launch times from weeks to minutes while building lasting shopper trust.
